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Kurita K, Obata T, Sutoh C, Matsuzawa D, Yoshinaga N, Kershaw J, Chhatkuli RB, Ota J, Shimizu E, Hirano Y. Individual cognitive therapy reduces frontal-thalamic resting-state functional connectivity in social anxiety disorder. Front Psychiatry 2023; 14:1233564. [PMID: 38179253 PMCID: PMC10764569 DOI: 10.3389/fpsyt.2023.1233564] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/02/2023] [Accepted: 12/01/2023] [Indexed: 01/06/2024] Open
Abstract
Introduction Previous neuroimaging studies in social anxiety disorders (SAD) have reported potential neural predictors of cognitive behavioral therapy (CBT)-related brain changes. However, several meta-analyses have demonstrated that cognitive therapy (CT) was superior to traditional exposure-based CBT for SAD. Objective To explore resting-state functional connectivity (rsFC) to evaluate the response to individual CT for SAD patients. Methods Twenty SAD patients who attended 16-week individual CT were scanned pre- and post-therapy along with twenty healthy controls (HCs). The severity of social anxiety was assessed with the Liebowitz Social Anxiety Scale (LSAS). Multi-voxel pattern analysis (MVPA) was performed on the pre-CT data to extract regions associated with a change in LSAS (∆LSAS). Group comparisons of the seed-based rsFC analysis were performed between the HCs and pre-CT patients and between the pre-and post-CT patients. Results MVPA-based regression analysis revealed that rsFC between the left thalamus and the frontal pole/inferior frontal gyrus was significantly correlated with ∆LSAS (adjusted R2 = 0.65; p = 0.00002). Compared with HCs, the pre-CT patients had higher rsFCs between the thalamus and temporal pole and between the thalamus and superior/middle temporal gyrus/planum temporale (p < 0.05). The rsFC between the thalamus and the frontal pole decreased post-CT (p < 0.05). Conclusion SAD patients had significant rsFC between the thalamus and temporal pole, superior/middle temporal gyrus, and planum temporale, which may be indicators of extreme anxiety in social situations. In addition, rsFC between the thalamus and the frontal pole may be a neuromarker for the effectiveness of individual CT.
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Affiliation(s)
- Kohei Kurita
- Research Center for Child Mental Development, Chiba University, Chiba, Japan
- United Graduate School of Child Development, Osaka University, Suita, Japan
| | - Takayuki Obata
- Research Center for Child Mental Development, Chiba University, Chiba, Japan
- Institute for Quantum Medical Science, National Institutes for Quantum and Radiological Science and Technology, Chiba, Japan
| | - Chihiro Sutoh
- Institute for Quantum Medical Science, National Institutes for Quantum and Radiological Science and Technology, Chiba, Japan
- Department of Cognitive Behavioral Physiology, Graduate School of Medicine, Chiba University, Chiba, Japan
| | - Daisuke Matsuzawa
- Research Center for Child Mental Development, Chiba University, Chiba, Japan
- United Graduate School of Child Development, Osaka University, Suita, Japan
- Institute for Quantum Medical Science, National Institutes for Quantum and Radiological Science and Technology, Chiba, Japan
| | - Naoki Yoshinaga
- Department of Cognitive Behavioral Physiology, Graduate School of Medicine, Chiba University, Chiba, Japan
- School of Nursing, Faculty of Medicine, University of Miyazaki, Miyazaki, Japan
| | - Jeff Kershaw
- Institute for Quantum Medical Science, National Institutes for Quantum and Radiological Science and Technology, Chiba, Japan
| | - Ritu Bhusal Chhatkuli
- Research Center for Child Mental Development, Chiba University, Chiba, Japan
- United Graduate School of Child Development, Osaka University, Suita, Japan
- Institute for Quantum Medical Science, National Institutes for Quantum and Radiological Science and Technology, Chiba, Japan
| | - Junko Ota
- Research Center for Child Mental Development, Chiba University, Chiba, Japan
- United Graduate School of Child Development, Osaka University, Suita, Japan
- Institute for Quantum Medical Science, National Institutes for Quantum and Radiological Science and Technology, Chiba, Japan
| | - Eiji Shimizu
- Research Center for Child Mental Development, Chiba University, Chiba, Japan
- United Graduate School of Child Development, Osaka University, Suita, Japan
- Institute for Quantum Medical Science, National Institutes for Quantum and Radiological Science and Technology, Chiba, Japan
- Department of Cognitive Behavioral Physiology, Graduate School of Medicine, Chiba University, Chiba, Japan
| | - Yoshiyuki Hirano
- Research Center for Child Mental Development, Chiba University, Chiba, Japan
- United Graduate School of Child Development, Osaka University, Suita, Japan
- Institute for Quantum Medical Science, National Institutes for Quantum and Radiological Science and Technology, Chiba, Japan
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2
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Boeken OJ, Cieslik EC, Langner R, Markett S. Characterizing functional modules in the human thalamus: coactivation-based parcellation and systems-level functional decoding. Brain Struct Funct 2023; 228:1811-1834. [PMID: 36547707 PMCID: PMC10516793 DOI: 10.1007/s00429-022-02603-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Accepted: 12/08/2022] [Indexed: 12/24/2022]
Abstract
The human thalamus relays sensory signals to the cortex and facilitates brain-wide communication. The thalamus is also more directly involved in sensorimotor and various cognitive functions but a full characterization of its functional repertoire, particularly in regard to its internal anatomical structure, is still outstanding. As a putative hub in the human connectome, the thalamus might reveal its functional profile only in conjunction with interconnected brain areas. We therefore developed a novel systems-level Bayesian reverse inference decoding that complements the traditional neuroinformatics approach towards a network account of thalamic function. The systems-level decoding considers the functional repertoire (i.e., the terms associated with a brain region) of all regions showing co-activations with a predefined seed region in a brain-wide fashion. Here, we used task-constrained meta-analytic connectivity-based parcellation (MACM-CBP) to identify thalamic subregions as seed regions and applied the systems-level decoding to these subregions in conjunction with functionally connected cortical regions. Our results confirm thalamic structure-function relationships known from animal and clinical studies and revealed further associations with language, memory, and locomotion that have not been detailed in the cognitive neuroscience literature before. The systems-level decoding further uncovered large systems engaged in autobiographical memory and nociception. We propose this novel decoding approach as a useful tool to detect previously unknown structure-function relationships at the brain network level, and to build viable starting points for future studies.
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Affiliation(s)
- Ole J Boeken
- Faculty of Life Sciences, Department of Molecular Psychology, Humboldt-Universität Zu Berlin, Rudower Chaussee 18, 12489, Berlin, Germany.
| | - Edna C Cieslik
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich, Jülich, Germany
| | - Robert Langner
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich, Jülich, Germany
| | - Sebastian Markett
- Faculty of Life Sciences, Department of Molecular Psychology, Humboldt-Universität Zu Berlin, Rudower Chaussee 18, 12489, Berlin, Germany
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3
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Yan H, Wu H, Cai Z, Du S, Li L, Xu B, Chang C, Wang N. The neural correlates of apathy in the context of aging and brain disorders: a meta-analysis of neuroimaging studies. Front Aging Neurosci 2023; 15:1181558. [PMID: 37396666 PMCID: PMC10311641 DOI: 10.3389/fnagi.2023.1181558] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Accepted: 06/05/2023] [Indexed: 07/04/2023] Open
Abstract
Introduction Apathy is a prevalent mood disturbance that occurs in a wide range of populations, including those with normal cognitive aging, mental disorders, neurodegenerative disorders and traumatic brain injuries. Recently, neuroimaging technologies have been employed to elucidate the neural substrates underlying brain disorders accompanying apathy. However, the consistent neural correlates of apathy across normal aging and brain disorders are still unclear. Methods This paper first provides a brief review of the neural mechanism of apathy in healthy elderly individuals, those with mental disorders, neurodegenerative disorders, and traumatic brain injuries. Further, following the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines, the structural and functional neuroimaging meta-analysis using activation likelihood estimation method is performed on the apathy group with brain disorders and the healthy elderly, aiming at exploring the neural correlates of apathy. Results The structural neuroimaging meta-analysis showed that gray matter atrophy is associated with apathy in the bilateral precentral gyrus (BA 13/6), bilateral insula (BA 47), bilateral medial frontal gyrus (BA 11), bilateral inferior frontal gyrus, left caudate (putamen) and right anterior cingulate, while the functional neuroimaging meta-analysis suggested that the functional connectivity in putamen and lateral globus pallidus is correlated with apathy. Discussion Through the neuroimaging meta-analysis, this study has identified the potential neural locations of apathy in terms of brain structure and function, which may offer valuable pathophysiological insights for developing more effective therapeutic interventions for affected patients.
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Affiliation(s)
- Hongjie Yan
- Department of Neurology, Affiliated Lianyungang Hospital of Xuzhou Medical University, Lianyungang, China
| | - Huijun Wu
- School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, China
- Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong, Hong Kong SAR, China
| | - Zenglin Cai
- Department of Neurology, Suzhou Hospital, Affiliated Hospital of Medical School, Nanjing University, Suzhou, China
- Department of Neurology, Gusu School, Suzhou Science and Technology Town Hospital, Nanjing Medical University, Suzhou, China
| | - Shouyun Du
- Department of Neurology, Guanyun People’s Hospital, Guanyun, China
| | - Lejun Li
- Department of Neurology, Suzhou TCM Hospital Affiliated to Nanjing University of Chinese Medicine, Suzhou, China
| | - Bingchao Xu
- Department of Neurology, Affiliated Lianyungang Hospital of Xuzhou Medical University, Lianyungang, China
| | - Chunqi Chang
- School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, China
- Pengcheng Laboratory, Shenzhen, China
| | - Nizhuan Wang
- School of Biomedical Engineering, ShanghaiTech University, Shanghai, China
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4
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Liu X, Eickhoff SB, Caspers S, Wu J, Genon S, Hoffstaedter F, Mars RB, Sommer IE, Eickhoff CR, Chen J, Jardri R, Reetz K, Dogan I, Aleman A, Kogler L, Gruber O, Caspers J, Mathys C, Patil KR. Functional parcellation of human and macaque striatum reveals human-specific connectivity in the dorsal caudate. Neuroimage 2021; 235:118006. [PMID: 33819611 PMCID: PMC8214073 DOI: 10.1016/j.neuroimage.2021.118006] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2020] [Revised: 02/10/2021] [Accepted: 03/17/2021] [Indexed: 12/12/2022] Open
Abstract
A wide homology between human and macaque striatum is often assumed as in both the striatum is involved in cognition, emotion and executive functions. However, differences in functional and structural organization between human and macaque striatum may reveal evolutionary divergence and shed light on human vulnerability to neuropsychiatric diseases. For instance, dopaminergic dysfunction of the human striatum is considered to be a pathophysiological underpinning of different disorders, such as Parkinson's disease (PD) and schizophrenia (SCZ). Previous investigations have found a wide similarity in structural connectivity of the striatum between human and macaque, leaving the cross-species comparison of its functional organization unknown. In this study, resting-state functional connectivity (RSFC) derived striatal parcels were compared based on their homologous cortico-striatal connectivity. The goal here was to identify striatal parcels whose connectivity is human-specific compared to macaque parcels. Functional parcellation revealed that the human striatum was split into dorsal, dorsomedial, and rostral caudate and ventral, central, and caudal putamen, while the macaque striatum was divided into dorsal, and rostral caudate and rostral, and caudal putamen. Cross-species comparison indicated dissimilar cortico-striatal RSFC of the topographically similar dorsal caudate. We probed clinical relevance of the striatal clusters by examining differences in their cortico-striatal RSFC and gray matter (GM) volume between patients (with PD and SCZ) and healthy controls. We found abnormal RSFC not only between dorsal caudate, but also between rostral caudate, ventral, central and caudal putamen and widespread cortical regions for both PD and SCZ patients. Also, we observed significant structural atrophy in rostral caudate, ventral and central putamen for both PD and SCZ while atrophy in the dorsal caudate was specific to PD. Taken together, our cross-species comparative results revealed shared and human-specific RSFC of different striatal clusters reinforcing the complex organization and function of the striatum. In addition, we provided a testable hypothesis that abnormalities in a region with human-specific connectivity, i.e., dorsal caudate, might be associated with neuropsychiatric disorders.
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Affiliation(s)
- Xiaojin Liu
- Institute of Neuroscience and Medicine (INM-7), Heinrich Heine University Düsseldorf, Düsseldorf, Germany; Institute of Systems Neuroscience, Research Centre Jülich, Jülich, Germany
| | - Simon B Eickhoff
- Institute of Neuroscience and Medicine (INM-7), Heinrich Heine University Düsseldorf, Düsseldorf, Germany; Institute of Systems Neuroscience, Research Centre Jülich, Jülich, Germany
| | - Svenja Caspers
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany; Institute for Anatomy I, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Jianxiao Wu
- Institute of Neuroscience and Medicine (INM-7), Heinrich Heine University Düsseldorf, Düsseldorf, Germany; Institute of Systems Neuroscience, Research Centre Jülich, Jülich, Germany
| | - Sarah Genon
- Institute of Neuroscience and Medicine (INM-7), Heinrich Heine University Düsseldorf, Düsseldorf, Germany; Institute of Systems Neuroscience, Research Centre Jülich, Jülich, Germany
| | - Felix Hoffstaedter
- Institute of Neuroscience and Medicine (INM-7), Heinrich Heine University Düsseldorf, Düsseldorf, Germany; Institute of Systems Neuroscience, Research Centre Jülich, Jülich, Germany
| | - Rogier B Mars
- Wellcome Centre for Integrative Neuroimaging, Centre for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, United Kingdom; Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Nijmegen, Netherlands
| | - Iris E Sommer
- Department of Biomedical Sciences of Cells & Systems, University Medical Center Groningen, Groningen, Netherlands
| | - Claudia R Eickhoff
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany; Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, University of Düsseldorf, Düsseldorf, Germany
| | - Ji Chen
- Institute of Neuroscience and Medicine (INM-7), Heinrich Heine University Düsseldorf, Düsseldorf, Germany; Institute of Systems Neuroscience, Research Centre Jülich, Jülich, Germany
| | - Renaud Jardri
- Division of Psychiatry, University of Lille, CNRS UMR9193, SCALab & CHU Lille, Fontan Hospital, CURE platform, Lille, France
| | - Kathrin Reetz
- JARA-BRAIN Institute Molecular Neuroscience and Neuroimaging, Forschungszentrum Jülich, RWTH Aachen University, Aachen, Germany; Department of Neurology, RWTH Aachen University, Aachen, Germany
| | - Imis Dogan
- JARA-BRAIN Institute Molecular Neuroscience and Neuroimaging, Forschungszentrum Jülich, RWTH Aachen University, Aachen, Germany; Department of Neurology, RWTH Aachen University, Aachen, Germany
| | - André Aleman
- Department of Neuroscience, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
| | - Lydia Kogler
- Department of Psychiatry and Psychotherapy, Medical School, University of Tübingen, Germany
| | - Oliver Gruber
- Section for Experimental Psychopathology and Neuroimaging, Department of General Psychiatry, Heidelberg University, Germany
| | - Julian Caspers
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany; Department of Diagnostic and Interventional Radiology, Medical Faculty, University of Düsseldorf, Düsseldorf, Germany
| | - Christian Mathys
- Department of Diagnostic and Interventional Radiology, Medical Faculty, University of Düsseldorf, Düsseldorf, Germany; Research Center Neurosensory Science, Carl von Ossietzky Universität Oldenburg, Oldenburg, Germany; Institute of Radiology and Neuroradiology, Evangelisches Krankenhaus, University of Oldenburg, Oldenburg, Germany
| | - Kaustubh R Patil
- Institute of Neuroscience and Medicine (INM-7), Heinrich Heine University Düsseldorf, Düsseldorf, Germany; Institute of Systems Neuroscience, Research Centre Jülich, Jülich, Germany.
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5
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Meta-analytic clustering dissociates brain activity and behavior profiles across reward processing paradigms. COGNITIVE AFFECTIVE & BEHAVIORAL NEUROSCIENCE 2021; 20:215-235. [PMID: 31872334 DOI: 10.3758/s13415-019-00763-7] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Reward learning is a ubiquitous cognitive mechanism guiding adaptive choices and behaviors, and when impaired, can lead to considerable mental health consequences. Reward-related functional neuroimaging studies have begun to implicate networks of brain regions essential for processing various peripheral influences (e.g., risk, subjective preference, delay, social context) involved in the multifaceted reward processing construct. To provide a more complete neurocognitive perspective on reward processing that synthesizes findings across the literature while also appreciating these peripheral influences, we used emerging meta-analytic techniques to elucidate brain regions, and in turn networks, consistently engaged in distinct aspects of reward processing. Using a data-driven, meta-analytic, k-means clustering approach, we dissociated seven meta-analytic groupings (MAGs) of neuroimaging results (i.e., brain activity maps) from 749 experimental contrasts across 176 reward processing studies involving 13,358 healthy participants. We then performed an exploratory functional decoding approach to gain insight into the putative functions associated with each MAG. We identified a seven-MAG clustering solution that represented dissociable patterns of convergent brain activity across reward processing tasks. Additionally, our functional decoding analyses revealed that each of these MAGs mapped onto discrete behavior profiles that suggested specialized roles in predicting value (MAG-1 & MAG-2) and processing a variety of emotional (MAG-3), external (MAG-4 & MAG-5), and internal (MAG-6 & MAG-7) influences across reward processing paradigms. These findings support and extend aspects of well-accepted reward learning theories and highlight large-scale brain network activity associated with distinct aspects of reward processing.
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Jackson RL, Bajada CJ, Lambon Ralph MA, Cloutman LL. The Graded Change in Connectivity across the Ventromedial Prefrontal Cortex Reveals Distinct Subregions. Cereb Cortex 2021; 30:165-180. [PMID: 31329834 PMCID: PMC7029692 DOI: 10.1093/cercor/bhz079] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2018] [Revised: 02/21/2019] [Accepted: 03/19/2019] [Indexed: 11/20/2022] Open
Abstract
The functional heterogeneity of the ventromedial prefrontal cortex (vmPFC) suggests it may include distinct functional subregions. To date these have not been well elucidated. Regions with differentiable connectivity (and as a result likely dissociable functions) may be identified using emergent data-driven approaches. However, prior parcellations of the vmPFC have only considered hard splits between distinct regions, although both hard and graded connectivity changes may exist. Here we determine the full pattern of change in structural and functional connectivity across the vmPFC for the first time and extract core distinct regions. Both structural and functional connectivity varied along a dorsomedial to ventrolateral axis from relatively dorsal medial wall regions to relatively lateral basal orbitofrontal cortex. The pattern of connectivity shifted from default mode network to sensorimotor and multimodal semantic connections. This finding extends the classical distinction between primate medial and orbital regions by demonstrating a similar gradient in humans for the first time. Additionally, core distinct regions in the medial wall and orbitofrontal cortex were identified that may show greater correspondence to functional differences than prior hard parcellations. The possible functional roles of the orbitofrontal cortex and medial wall are discussed.
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Affiliation(s)
- Rebecca L Jackson
- Medical Research Council Cognition & Brain Sciences Unit, University of Cambridge, Cambridge, UK
| | - Claude J Bajada
- Faculty of Medicine and Surgery, University of Malta, Msida, MSD, Malta
| | - Matthew A Lambon Ralph
- Medical Research Council Cognition & Brain Sciences Unit, University of Cambridge, Cambridge, UK
| | - Lauren L Cloutman
- Neuroscience and Aphasia Research Unit (NARU), Division of Neuroscience & Experimental Psychology (Zochonis Building), University of Manchester, Manchester, UK
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7
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Functional parcellation of the default mode network: a large-scale meta-analysis. Sci Rep 2020; 10:16096. [PMID: 32999307 PMCID: PMC7528067 DOI: 10.1038/s41598-020-72317-8] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2020] [Accepted: 08/19/2020] [Indexed: 11/08/2022] Open
Abstract
The default mode network (DMN) consists of several regions that selectively interact to support distinct domains of cognition. Of the various sites that partake in DMN function, the posterior cingulate cortex (PCC), temporal parietal junction (TPJ), and medial prefrontal cortex (MPFC) are frequently identified as key contributors. Yet, it remains unclear whether these subcomponents of the DMN make unique contributions to specific cognitive processes and health conditions. To address this issue, we applied a meta-analytic parcellation approach used in prior work. This approach used the Neurosynth database and classification methods to quantify the association between PCC, TPJ, and MPFC activation and specific topics related to cognition and health (e.g., decision making and smoking). Our analyses replicated prior observations that the PCC, TPJ, and MPFC collectively support multiple cognitive functions such as decision making, memory, and awareness. To gain insight into the functional organization of each region, we parceled each region based on its coactivation pattern with the rest of the brain. This analysis indicated that each region could be further subdivided into functionally distinct subcomponents. Taken together, we further delineate DMN function by demonstrating the relative strengths of association among subcomponents across a range of cognitive processes and health conditions. A continued attentiveness to the specialization within the DMN allows future work to consider the nuances in sub-regional contributions necessary for healthy cognition, as well as create the potential for more targeted treatment protocols in various health conditions.
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Rosa MGP, Soares JGM, Chaplin TA, Majka P, Bakola S, Phillips KA, Reser DH, Gattass R. Cortical Afferents of Area 10 in Cebus Monkeys: Implications for the Evolution of the Frontal Pole. Cereb Cortex 2020; 29:1473-1495. [PMID: 29697775 DOI: 10.1093/cercor/bhy044] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2017] [Revised: 01/12/2018] [Accepted: 02/07/2018] [Indexed: 01/26/2023] Open
Abstract
Area 10, located in the frontal pole, is a unique specialization of the primate cortex. We studied the cortical connections of area 10 in the New World Cebus monkey, using injections of retrograde tracers in different parts of this area. We found that injections throughout area 10 labeled neurons in a consistent set of areas in the dorsolateral, ventrolateral, orbital, and medial parts of the frontal cortex, superior temporal association cortex, and posterior cingulate/retrosplenial region. However, sites on the midline surface of area 10 received more substantial projections from the temporal lobe, including clear auditory connections, whereas those in more lateral parts received >90% of their afferents from other frontal areas. This difference in anatomical connectivity reflects functional connectivity findings in the human brain. The pattern of connections in Cebus is very similar to that observed in the Old World macaque monkey, despite >40 million years of evolutionary separation, but lacks some of the connections reported in the more closely related but smaller marmoset monkey. These findings suggest that the clearer segregation observed in the human frontal pole reflects regional differences already present in early simian primates, and that overall brain mass influences the pattern of cortico-cortical connectivity.
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Affiliation(s)
- Marcello G P Rosa
- Department of Physiology, Monash University, Clayton, VIC, Australia.,Neuroscience Program, Biomedicine Research Institute, Monash University, Clayton, VIC, Australia.,Australian Research Council, Centre of Excellence for Integrative Brain Function, Monash University Node, Clayton, VIC, Australia
| | - Juliana G M Soares
- Programa de Neurobiologia, Instituto de Biofísica Carlos Chagas Filho, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil
| | - Tristan A Chaplin
- Department of Physiology, Monash University, Clayton, VIC, Australia.,Neuroscience Program, Biomedicine Research Institute, Monash University, Clayton, VIC, Australia.,Australian Research Council, Centre of Excellence for Integrative Brain Function, Monash University Node, Clayton, VIC, Australia
| | - Piotr Majka
- Department of Physiology, Monash University, Clayton, VIC, Australia.,Neuroscience Program, Biomedicine Research Institute, Monash University, Clayton, VIC, Australia.,Australian Research Council, Centre of Excellence for Integrative Brain Function, Monash University Node, Clayton, VIC, Australia.,Laboratory of Neuroinformatics, Department of Neurophysiology, Nencki Institute of Experimental Biology of Polish Academy of Sciences, 3 Pasteur Street, Warsaw, Poland
| | - Sophia Bakola
- Department of Physiology, Monash University, Clayton, VIC, Australia.,Neuroscience Program, Biomedicine Research Institute, Monash University, Clayton, VIC, Australia.,Australian Research Council, Centre of Excellence for Integrative Brain Function, Monash University Node, Clayton, VIC, Australia.,Department of Pharmacy and Biotechnology, University of Bologna, Bologna, Italy
| | - Kimberley A Phillips
- Department of Psychology, Trinity University, San Antonio, TX, USA.,USA Southwest National Primate Research Center, Texas Biomedical Research Institute, San Antonio, TX, USA
| | - David H Reser
- Department of Physiology, Monash University, Clayton, VIC, Australia.,Neuroscience Program, Biomedicine Research Institute, Monash University, Clayton, VIC, Australia.,Australian Research Council, Centre of Excellence for Integrative Brain Function, Monash University Node, Clayton, VIC, Australia.,Monash Rural Health, Monash University, Churchill, VIC, Australia
| | - Ricardo Gattass
- Programa de Neurobiologia, Instituto de Biofísica Carlos Chagas Filho, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil
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9
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Chase HW, Grace AA, Fox PT, Phillips ML, Eickhoff SB. Functional differentiation in the human ventromedial frontal lobe: A data-driven parcellation. Hum Brain Mapp 2020; 41:3266-3283. [PMID: 32314470 PMCID: PMC7375078 DOI: 10.1002/hbm.25014] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2019] [Revised: 03/06/2020] [Accepted: 04/07/2020] [Indexed: 12/18/2022] Open
Abstract
Ventromedial regions of the frontal lobe (vmFL) are thought to play a key role in decision-making and emotional regulation. However, aspects of this area's functional organization, including the presence of a multiple subregions, their functional and anatomical connectivity, and the cross-species homologies of these subregions with those of other species, remain poorly understood. To address this uncertainty, we employed a two-stage parcellation of the region to identify six distinct structures within the region on the basis of data-driven classification of functional connectivity patterns obtained using the meta-analytic connectivity modeling (MACM) approach. From anterior to posterior, the derived subregions included two lateralized posterior regions, an intermediate posterior region, a dorsal and ventral central region, and a single anterior region. The regions were characterized further by functional connectivity derived using resting-state fMRI and functional decoding using the Brain Map database. In general, the regions could be differentiated on the basis of different patterns of functional connectivity with canonical "default mode network" regions and/or subcortical regions such as the striatum. Together, the findings suggest the presence of functionally distinct neural structures within vmFL, consistent with data from experimental animals as well prior demonstrations of anatomical differences within the region. Detailed correspondence with the anterior cingulate, medial orbitofrontal cortex, and rostroventral prefrontal cortex, as well as specific animal homologs are discussed. The findings may suggest future directions for resolving potential functional and structural correspondence of subregions within the frontal lobe across behavioral contexts, and across mammalian species.
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Affiliation(s)
- Henry W Chase
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | - Anthony A Grace
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA.,Department of Neuroscience and Psychology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Peter T Fox
- Research Imaging Institute, University of Texas Health Science Center, San Antonio, Texas, USA.,Department of Radiology, University of Texas Health Science Center, San Antonio, Texas, USA.,Department of Psychiatry, University of Texas Health Science Center, San Antonio, Texas, USA.,Research and Development Service, South Texas Veterans Health Care System, San Antonio, Texas, USA
| | - Mary L Phillips
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | - Simon B Eickhoff
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany.,Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
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10
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Xu J, Wang C, Xu Z, Li T, Chen F, Chen K, Gao J, Wang J, Hu Q. Specific Functional Connectivity Patterns of Middle Temporal Gyrus Subregions in Children and Adults with Autism Spectrum Disorder. Autism Res 2019; 13:410-422. [PMID: 31729198 DOI: 10.1002/aur.2239] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2019] [Revised: 10/12/2019] [Accepted: 10/14/2019] [Indexed: 02/02/2023]
Abstract
As one of the key regions in the "social brain" network, the middle temporal gyrus (MTG) has been widely reported to be associated with autism spectrum disorder (ASD), but there have been contradictory results in terms of whether it shows hyperconnectivity or hypoconnectivity. Delineating roles of MTG at the subregional level may eliminate the observed inconsistencies and provide a new avenue to reveal the neurophysiologic mechanism of ASD. Thus, we first performed connectivity-based parcellation using the BrainMap database to identify fine-grained functional topography of the MTG. Then, the MTG subregions were used to investigate differences in the functional connectivity in children and adults with ASD using two data sets from Autism Brain Imaging Data Exchange database. Four distinct subregions in the human left and right MTG were identified, including the anterior MTG (aMTG), middle-anterior MTG (maMTG), middle-posterior MTG, and posterior MTG (pMTG). The bilateral pMTG was more vulnerable in both children and adults with ASD than in the typically developing (TD) group, mainly showing hypoconnectivity with different brain regions. In addition, the bilateral aMTG and right maMTG also showed altered functional connectivity in adults with ASD compared to the TD group. Moreover, all these altered MTG subregions were mainly associated with social cognition and language, as revealed by functional characterization. Further correlation analyses also showed trends of association between altered connectivity of the left aMTG and the Autism Diagnostic Observation Schedule scores in adults with ASD. Together, these results suggest a potential objective way to explore sub-regional differences associated with such disorders. Autism Res 2020, 13: 410-422. © 2019 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: Four distinct subregions in the human left and right middle temporal gyrus (MTG) were identified, including the anterior MTG (aMTG), middle-anterior MTG (maMTG), middle-posterior MTG, and posterior MTG (pMTG). The bilateral pMTG was more vulnerable in both children and adults with autism spectrum disorder (ASD) than in the typically developing (TD) group, mainly showing hypoconnectivity with different brain regions. In addition, the bilateral aMTG and right maMTG also showed altered functional connectivity in adults with ASD compared to the TD group. Moreover, all these altered MTG subregions were mainly associated with social cognition and language, as revealed by functional characterization. Further correlation analyses also showed trends of association between altered connectivity of the left aMTG and the Autism Diagnostic Observation Schedule scores in adults with ASD.
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Affiliation(s)
- Jinping Xu
- Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.,University of Chinese Academy of Sciences, Beijing, China
| | - Chao Wang
- School of Psychology, Shenzhen University, Shenzhen, China.,Shenzhen Key Laboratory of Affective and Social Cognitive Science, Shenzhen University, Shenzhen, China
| | - Ziyun Xu
- Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Tian Li
- Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Fangfang Chen
- College of Mathematics and Statistics, Shenzhen University, Shenzhen, China
| | - Kai Chen
- School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, China
| | - Jingjing Gao
- School of Information and Communication Engineer, University of Electronic Science and Technology of China, Chengdu, China
| | - Jiaojian Wang
- Key Laboratory for Neuroinformation of the Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Qingmao Hu
- Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
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11
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de la Vega A, Yarkoni T, Wager TD, Banich MT. Large-scale Meta-analysis Suggests Low Regional Modularity in Lateral Frontal Cortex. Cereb Cortex 2019; 28:3414-3428. [PMID: 28968758 DOI: 10.1093/cercor/bhx204] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2017] [Accepted: 07/20/2017] [Indexed: 01/24/2023] Open
Abstract
Extensive fMRI study of human lateral frontal cortex (LFC) has yet to yield a consensus mapping between discrete anatomy and psychological states, partly due to the difficulty of inferring mental states from brain activity. Despite this, there have been few large-scale efforts to map the full range of psychological states across the entirety of LFC. Here, we used a data-driven approach to generate a comprehensive functional-anatomical mapping of LFC from 11 406 neuroimaging studies. We identified putatively separable LFC regions on the basis of whole-brain co-activation, revealing 14 clusters organized into 3 whole-brain networks. Next, we generated functional preference profiles by using multivariate classification to identify the psychological states that best predicted activity within each cluster. We observed large functional differences between networks, suggesting brain networks support distinct modes of processing. Within each network, however, we observed relatively low functional specificity, suggesting discrete psychological states are not strongly localized to individual regions; instead, our results are consistent with the view that individual LFC regions work as part of distributed networks to give rise to flexible behavior. Collectively, our results provide a comprehensive synthesis of a diverse neuroimaging literature using relatively unbiased data-driven methods.
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Affiliation(s)
- Alejandro de la Vega
- Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, CO, USA.,Institute of Cognitive Science, University of Colorado Boulder, Boulder, CO, USA.,Department of Psychology, University of Texas at Austin, Austin, TX, USA
| | - Tal Yarkoni
- Department of Psychology, University of Texas at Austin, Austin, TX, USA
| | - Tor D Wager
- Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, CO, USA.,Institute of Cognitive Science, University of Colorado Boulder, Boulder, CO, USA
| | - Marie T Banich
- Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, CO, USA.,Institute of Cognitive Science, University of Colorado Boulder, Boulder, CO, USA
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12
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Rieiro H, Diaz-Piedra C, Morales JM, Catena A, Romero S, Roca-Gonzalez J, Fuentes LJ, Di Stasi LL. Validation of Electroencephalographic Recordings Obtained with a Consumer-Grade, Single Dry Electrode, Low-Cost Device: A Comparative Study. SENSORS (BASEL, SWITZERLAND) 2019; 19:E2808. [PMID: 31234599 PMCID: PMC6630628 DOI: 10.3390/s19122808] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/29/2019] [Revised: 06/15/2019] [Accepted: 06/20/2019] [Indexed: 12/25/2022]
Abstract
The functional validity of the signal obtained with low-cost electroencephalography (EEG) devices is still under debate. Here, we have conducted an in-depth comparison of the EEG-recordings obtained with a medical-grade golden-cup electrodes ambulatory device, the SOMNOwatch + EEG-6, vs those obtained with a consumer-grade, single dry electrode low-cost device, the NeuroSky MindWave, one of the most affordable devices currently available. We recorded EEG signals at Fp1 using the two different devices simultaneously on 21 participants who underwent two experimental phases: a 12-minute resting state task (alternating two cycles of closed/open eyes periods), followed by 60-minute virtual-driving task. We evaluated the EEG recording quality by comparing the similarity between the temporal data series, their spectra, their signal-to-noise ratio, the reliability of EEG measurements (comparing the closed eyes periods), as well as their blink detection rate. We found substantial agreement between signals: whereas, qualitatively, the NeuroSky MindWave presented higher levels of noise and a biphasic shape of blinks, the similarity metric indicated that signals from both recording devices were significantly correlated. While the NeuroSky MindWave was less reliable, both devices had a similar blink detection rate. Overall, the NeuroSky MindWave is noise-limited, but provides stable recordings even through long periods of time. Furthermore, its data would be of adequate quality compared to that of conventional wet electrode EEG devices, except for a potential calibration error and spectral differences at low frequencies.
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Affiliation(s)
- Héctor Rieiro
- Department of Signal Theory and Communications, University of Vigo, 36310 Vigo, Spain.
- Mind, Brain, and Behavior Research Center, University of Granada, 18071 Granada, Spain.
| | - Carolina Diaz-Piedra
- Mind, Brain, and Behavior Research Center, University of Granada, 18071 Granada, Spain.
- College of Nursing and Health Innovation, Arizona State University, Phoenix, AZ 85004, USA.
| | - José Miguel Morales
- Mind, Brain, and Behavior Research Center, University of Granada, 18071 Granada, Spain.
- Department of Computer Architecture and Technology, University of Granada, 18071 Granada, Spain.
| | - Andrés Catena
- Mind, Brain, and Behavior Research Center, University of Granada, 18071 Granada, Spain.
| | - Samuel Romero
- Department of Computer Architecture and Technology, University of Granada, 18071 Granada, Spain.
| | - Joaquin Roca-Gonzalez
- Department of Bioengineering, Technical University of Cartagena, 30202 Cartagena, Spain.
| | - Luis J Fuentes
- Department of Basic Psychology and Methodology, University of Murcia, 30100 Murcia, Spain.
| | - Leandro L Di Stasi
- Mind, Brain, and Behavior Research Center, University of Granada, 18071 Granada, Spain.
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13
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Subspecialization within default mode nodes characterized in 10,000 UK Biobank participants. Proc Natl Acad Sci U S A 2018; 115:12295-12300. [PMID: 30420501 PMCID: PMC6275484 DOI: 10.1073/pnas.1804876115] [Citation(s) in RCA: 87] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023] Open
Abstract
The human default mode network (DMN) is implicated in several unique mental capacities. In this study, we tested whether brain-wide interregional communication in the DMN can be derived from population variability in intrinsic activity fluctuations, gray-matter morphology, and fiber tract anatomy. In a sample of 10,000 UK Biobank participants, pattern-learning algorithms revealed functional coupling states in the DMN that are linked to connectivity profiles between other macroscopical brain networks. In addition, DMN gray matter volume was covaried with white matter microstructure of the fornix. Collectively, functional and structural patterns unmasked a possible division of labor within major DMN nodes: Subregions most critical for cortical network interplay were adjacent to subregions most predictive of fornix fibers from the hippocampus that processes memories and places.
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14
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Neural correlates of apathy in patients with neurodegenerative disorders: an activation likelihood estimation (ALE) meta-analysis. Brain Imaging Behav 2018; 13:1815-1834. [DOI: 10.1007/s11682-018-9959-0] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/14/2023]
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15
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Mattan BD, Kubota JT, Li T, Dang TP, Cloutier J. Motivation Modulates Brain Networks in Response to Faces Varying in Race and Status: A Multivariate Approach. eNeuro 2018; 5:ENEURO.0039-18.2018. [PMID: 30225341 PMCID: PMC6140103 DOI: 10.1523/eneuro.0039-18.2018] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2018] [Revised: 08/05/2018] [Accepted: 08/06/2018] [Indexed: 01/27/2023] Open
Abstract
Previous behavioral and neuroimaging work indicates that individuals who are externally motivated to respond without racial prejudice tend not to spontaneously regulate their prejudice and prefer to focus on nonracial attributes when evaluating others. This fMRI multivariate analysis used partial least squares analysis to examine the distributed neural processing of race and a relevant but ostensibly nonracial attribute (i.e., socioeconomic status) as a function of the perceiver's external motivation. Sixty-one white male participants (Homo sapiens) privately formed impressions of black and white male faces ascribed with high or low status. Across all conditions, greater external motivation was associated with reduced coactivation of brain regions believed to support emotion regulation (rostral anterior cingulate cortex), introspection (middle cingulate), and social cognition (temporal pole, medial prefrontal cortex). The reduced involvement of this network irrespective of target race and status suggests that external motivation is related to the participant's overall approach to impression formation in an interracial context. The findings highlight the importance of examining network coactivation in understanding the role of external motivation in impression formation, among other interracial social processes.
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Affiliation(s)
- Bradley D. Mattan
- Department of Psychological and Brain Sciences, University of Delaware, Newark, Delaware 19716
| | - Jennifer T. Kubota
- Department of Psychological and Brain Sciences, University of Delaware, Newark, Delaware 19716
- Department of Political Science and International Relations, University of Delaware, Newark, Delaware 19716
| | - Tianyi Li
- College of Business Administration, University of Illinois at Chicago, Chicago, Illinois 60607
| | - Tzipporah P. Dang
- Department of Psychological and Brain Sciences, University of Delaware, Newark, Delaware 19716
| | - Jasmin Cloutier
- Department of Psychological and Brain Sciences, University of Delaware, Newark, Delaware 19716
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16
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Hartwigsen G, Neef NE, Camilleri JA, Margulies DS, Eickhoff SB. Functional Segregation of the Right Inferior Frontal Gyrus: Evidence From Coactivation-Based Parcellation. Cereb Cortex 2018; 29:1532-1546. [DOI: 10.1093/cercor/bhy049] [Citation(s) in RCA: 61] [Impact Index Per Article: 10.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2017] [Revised: 02/13/2018] [Accepted: 02/14/2018] [Indexed: 12/19/2022] Open
Affiliation(s)
- Gesa Hartwigsen
- Research Group Modulation of Language Networks, Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Nicole E Neef
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Julia A Camilleri
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Institute of Neuroscience and Medicine, Brain & Behavior (INM-7), Research Centre Jülich, Jülich, Germany
| | - Daniel S Margulies
- Frontlab, Institut du Cerveau et de la Moelle épinière (ICM), UPMC UMRS 1127, Inserm U 1127, CNRS UMR 7225, Paris, France
| | - Simon B Eickhoff
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Institute of Neuroscience and Medicine, Brain & Behavior (INM-7), Research Centre Jülich, Jülich, Germany
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17
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Wang Y, Chen W, Ye L, Biswal BB, Yang X, Zou Q, Yang P, Yang Q, Wang X, Cui Q, Duan X, Liao W, Chen H. Multiscale energy reallocation during low-frequency steady-state brain response. Hum Brain Mapp 2018; 39:2121-2132. [PMID: 29389047 DOI: 10.1002/hbm.23992] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2017] [Revised: 01/16/2018] [Accepted: 01/24/2018] [Indexed: 01/01/2023] Open
Abstract
Traditional task-evoked brain activations are based on detection and estimation of signal change from the mean signal. By contrast, the low-frequency steady-state brain response (lfSSBR) reflects frequency-tagging activity at the fundamental frequency of the task presentation and its harmonics. Compared to the activity at these resonant frequencies, brain responses at nonresonant frequencies are largely unknown. Additionally, because the lfSSBR is defined by power change, we hypothesize using Parseval's theorem that the power change reflects brain signal variability rather than the change of mean signal. Using a face recognition task, we observed power increase at the fundamental frequency (0.05 Hz) and two harmonics (0.1 and 0.15 Hz) and power decrease within the infra-slow frequency band (<0.1 Hz), suggesting a multifrequency energy reallocation. The consistency of power and variability was demonstrated by the high correlation (r > .955) of their spatial distribution and brain-behavior relationship at all frequency bands. Additionally, the reallocation of finite energy was observed across various brain regions and frequency bands, forming a particular spatiotemporal pattern. Overall, results from this study strongly suggest that frequency-specific power and variability may measure the same underlying brain activity and that these results may shed light on different mechanisms between lfSSBR and brain activation, and spatiotemporal characteristics of energy reallocation induced by cognitive tasks.
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Affiliation(s)
- Yifeng Wang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, 611731, China.,School of Life Science and Technology, Center for Information in BioMedicine, University of Electronic Science and Technology of China, Chengdu, 611731, China
| | - Wang Chen
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, 611731, China.,School of Life Science and Technology, Center for Information in BioMedicine, University of Electronic Science and Technology of China, Chengdu, 611731, China
| | - Liangkai Ye
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, 611731, China.,School of Life Science and Technology, Center for Information in BioMedicine, University of Electronic Science and Technology of China, Chengdu, 611731, China
| | - Bharat B Biswal
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, 611731, China.,School of Life Science and Technology, Center for Information in BioMedicine, University of Electronic Science and Technology of China, Chengdu, 611731, China.,Department of Biomedical Engineering, New Jersey Institute of Technology, 607 Fenster Hall, University Height, Newark, New Jersey, 07102
| | - Xuezhi Yang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, 611731, China.,School of Life Science and Technology, Center for Information in BioMedicine, University of Electronic Science and Technology of China, Chengdu, 611731, China
| | - Qijun Zou
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, 611731, China.,School of Life Science and Technology, Center for Information in BioMedicine, University of Electronic Science and Technology of China, Chengdu, 611731, China
| | - Pu Yang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, 611731, China.,School of Life Science and Technology, Center for Information in BioMedicine, University of Electronic Science and Technology of China, Chengdu, 611731, China
| | - Qi Yang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, 611731, China.,School of Life Science and Technology, Center for Information in BioMedicine, University of Electronic Science and Technology of China, Chengdu, 611731, China
| | - Xinqi Wang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, 611731, China.,School of Life Science and Technology, Center for Information in BioMedicine, University of Electronic Science and Technology of China, Chengdu, 611731, China
| | - Qian Cui
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, 611731, China.,School of Political Science and Public Administration, University of Electronic Science and Technology of China, Chengdu, 611731, China
| | - Xujun Duan
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, 611731, China.,School of Life Science and Technology, Center for Information in BioMedicine, University of Electronic Science and Technology of China, Chengdu, 611731, China
| | - Wei Liao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, 611731, China.,School of Life Science and Technology, Center for Information in BioMedicine, University of Electronic Science and Technology of China, Chengdu, 611731, China
| | - Huafu Chen
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, 611731, China.,School of Life Science and Technology, Center for Information in BioMedicine, University of Electronic Science and Technology of China, Chengdu, 611731, China
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18
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Peng K, Steele SC, Becerra L, Borsook D. Brodmann area 10: Collating, integrating and high level processing of nociception and pain. Prog Neurobiol 2017; 161:1-22. [PMID: 29199137 DOI: 10.1016/j.pneurobio.2017.11.004] [Citation(s) in RCA: 46] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2017] [Revised: 11/16/2017] [Accepted: 11/28/2017] [Indexed: 02/08/2023]
Abstract
Multiple frontal cortical brain regions have emerged as being important in pain processing, whether it be integrative, sensory, cognitive, or emotional. One such region, Brodmann Area 10 (BA 10), is the largest frontal brain region that has been shown to be involved in a wide variety of functions including risk and decision making, odor evaluation, reward and conflict, pain, and working memory. BA 10, also known as the anterior prefrontal cortex, frontopolar prefrontal cortex or rostral prefrontal cortex, is comprised of at least two cytoarchitectonic sub-regions, medial and lateral. To date, the explicit role of BA 10 in the processing of pain hasn't been fully elucidated. In this paper, we first review the anatomical pathways and functional connectivity of BA 10. Numerous functional imaging studies of experimental or clinical pain have also reported brain activations and/or deactivations in BA 10 in response to painful events. The evidence suggests that BA 10 may play a critical role in the collation, integration and high-level processing of nociception and pain, but also reveals possible functional distinctions between the subregions of BA 10 in this process.
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Affiliation(s)
- Ke Peng
- Center for Pain and the Brain, Harvard Medical School, Boston, MA, United States; Department of Anesthesiology, Perioperative and Pain Medicine, Boston Children's Hospital, Boston, MA, United States; Department of Psychiatry and Radiology, Massachusetts General Hospital, Charlestown, MA, United States.
| | - Sarah C Steele
- Center for Pain and the Brain, Harvard Medical School, Boston, MA, United States; Department of Anesthesiology, Perioperative and Pain Medicine, Boston Children's Hospital, Boston, MA, United States; Department of Psychiatry and Radiology, Massachusetts General Hospital, Charlestown, MA, United States
| | - Lino Becerra
- Center for Pain and the Brain, Harvard Medical School, Boston, MA, United States; Department of Anesthesiology, Perioperative and Pain Medicine, Boston Children's Hospital, Boston, MA, United States; Department of Psychiatry and Radiology, Massachusetts General Hospital, Charlestown, MA, United States; Department of Psychiatry, Mclean Hospital, Belmont, MA, United States
| | - David Borsook
- Center for Pain and the Brain, Harvard Medical School, Boston, MA, United States; Department of Anesthesiology, Perioperative and Pain Medicine, Boston Children's Hospital, Boston, MA, United States; Department of Psychiatry and Radiology, Massachusetts General Hospital, Charlestown, MA, United States; Department of Psychiatry, Mclean Hospital, Belmont, MA, United States
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19
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Mansouri FA, Koechlin E, Rosa MGP, Buckley MJ. Managing competing goals — a key role for the frontopolar cortex. Nat Rev Neurosci 2017; 18:645-657. [DOI: 10.1038/nrn.2017.111] [Citation(s) in RCA: 155] [Impact Index Per Article: 22.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
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20
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Xia X, Fan L, Cheng C, Eickhoff SB, Chen J, Li H, Jiang T. Multimodal connectivity-based parcellation reveals a shell-core dichotomy of the human nucleus accumbens. Hum Brain Mapp 2017; 38:3878-3898. [PMID: 28548226 DOI: 10.1002/hbm.23636] [Citation(s) in RCA: 30] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2016] [Revised: 04/14/2017] [Accepted: 04/21/2017] [Indexed: 12/21/2022] Open
Abstract
The subdifferentiation of the nucleus accumbens (NAc) has been extensively studied using neuroanatomy and histochemistry, yielding a well-accepted dichotomic shell/core architecture that reflects dissociable roles, such as in reward and aversion, respectively. However, in vivo parcellation of these structures in humans has been rare, potentially impairing future research into the structural and functional characteristics and alterations of putative NAc subregions. Here, we used three complementary parcellation schemes based on tractography, task-independent functional connectivity, and task-dependent co-activation to investigate the regional differentiation within the NAc. We found that a 2-cluster solution with shell-like and core-like subdivisions provided the best description of the data and was consistent with the earlier anatomical shell/core architecture. The consensus clusters from this optimal solution, which was based on the three schemes, were used as the final parcels for the subsequent connection analyses. The resulting connectivity patterns presented inter-hemispheric symmetry, convergence and divergence across the modalities, and, most importantly, clearly distinct patterns between the two subregions. This convergent connectivity patterns also confirmed the connections in animal models, supporting views that the two subregions could have antagonistic roles in some circumstances. Finally, the identified parcels should be helpful in further neuroimaging studies of the NAc. Hum Brain Mapp 38:3878-3898, 2017. © 2017 Wiley Periodicals, Inc.
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Affiliation(s)
- Xiaoluan Xia
- College of Computer Science and Technology, Taiyuan University of Technology, Taiyuan, 030600, China
| | - Lingzhong Fan
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China
| | - Chen Cheng
- College of Computer Science and Technology, Taiyuan University of Technology, Taiyuan, 030600, China
| | - Simon B Eickhoff
- Institute of Neuroscience and Medicine (INM-1), Research Centre Juelich, 52425 Juelich, Germany.,Institute for Clinical Neuroscience and Medical Psychology, Heinrich-Heine-University Düsseldorf, Düsseldorf, 40225, Germany
| | - Junjie Chen
- College of Computer Science and Technology, Taiyuan University of Technology, Taiyuan, 030600, China
| | - Haifang Li
- College of Computer Science and Technology, Taiyuan University of Technology, Taiyuan, 030600, China
| | - Tianzi Jiang
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China.,National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China.,CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China.,The Queensland Brain Institute, University of Queensland, Brisbane, QLD, 4072, Australia
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21
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Laird AR, Riedel MC, Okoe M, Jianu R, Ray KL, Eickhoff SB, Smith SM, Fox PT, Sutherland MT. Heterogeneous fractionation profiles of meta-analytic coactivation networks. Neuroimage 2017; 149:424-435. [PMID: 28222386 PMCID: PMC5408583 DOI: 10.1016/j.neuroimage.2016.12.037] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2015] [Revised: 12/01/2016] [Accepted: 12/14/2016] [Indexed: 11/22/2022] Open
Abstract
Computational cognitive neuroimaging approaches can be leveraged to characterize the hierarchical organization of distributed, functionally specialized networks in the human brain. To this end, we performed large-scale mining across the BrainMap database of coordinate-based activation locations from over 10,000 task-based experiments. Meta-analytic coactivation networks were identified by jointly applying independent component analysis (ICA) and meta-analytic connectivity modeling (MACM) across a wide range of model orders (i.e., d=20-300). We then iteratively computed pairwise correlation coefficients for consecutive model orders to compare spatial network topologies, ultimately yielding fractionation profiles delineating how "parent" functional brain systems decompose into constituent "child" sub-networks. Fractionation profiles differed dramatically across canonical networks: some exhibited complex and extensive fractionation into a large number of sub-networks across the full range of model orders, whereas others exhibited little to no decomposition as model order increased. Hierarchical clustering was applied to evaluate this heterogeneity, yielding three distinct groups of network fractionation profiles: high, moderate, and low fractionation. BrainMap-based functional decoding of resultant coactivation networks revealed a multi-domain association regardless of fractionation complexity. Rather than emphasize a cognitive-motor-perceptual gradient, these outcomes suggest the importance of inter-lobar connectivity in functional brain organization. We conclude that high fractionation networks are complex and comprised of many constituent sub-networks reflecting long-range, inter-lobar connectivity, particularly in fronto-parietal regions. In contrast, low fractionation networks may reflect persistent and stable networks that are more internally coherent and exhibit reduced inter-lobar communication.
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Affiliation(s)
- Angela R Laird
- Department of Physics, Florida International University, Miami, FL, USA.
| | - Michael C Riedel
- Department of Physics, Florida International University, Miami, FL, USA
| | - Mershack Okoe
- School of Computing and Information Sciences, Florida International University, Miami, FL, USA
| | - Radu Jianu
- School of Computing and Information Sciences, Florida International University, Miami, FL, USA
| | - Kimberly L Ray
- Research Imaging Center, University of California Davis, Sacramento, CA, USA
| | - Simon B Eickhoff
- Institute of Clinical Neuroscience and Medical Psychology, Heinrich-Heine University, Düsseldorf, Germany; Institute of Neuroscience and Medicine, Research Center Jülich, Jülich, Germany
| | - Stephen M Smith
- Oxford Centre for Functional MRI of the Brain, University of Oxford, Oxford, UK
| | - Peter T Fox
- Research Imaging Institute, University of Texas Health Science Center, San Antonio, TX, USA; Research Service, South Texas Veterans Administration Medical Center, San Antonio, TX, USA; State Key Laboratory for Brain and Cognitive Sciences, University of Hong Kong, Hong Kong
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22
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Eickhoff SB, Constable RT, Yeo BTT. Topographic organization of the cerebral cortex and brain cartography. Neuroimage 2017; 170:332-347. [PMID: 28219775 DOI: 10.1016/j.neuroimage.2017.02.018] [Citation(s) in RCA: 93] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2016] [Revised: 02/02/2017] [Accepted: 02/07/2017] [Indexed: 01/17/2023] Open
Abstract
One of the most specific but also challenging properties of the brain is its topographic organization into distinct modules or cortical areas. In this paper, we first review the concept of topographic organization and its historical development. Next, we provide a critical discussion of the current definition of what constitutes a cortical area, why the concept has been so central to the field of neuroimaging and the challenges that arise from this view. A key aspect in this discussion is the issue of spatial scale and hierarchy in the brain. Focusing on in-vivo brain parcellation as a rapidly expanding field of research, we highlight potential limitations of the classical concept of cortical areas in the context of multi-modal parcellation and propose a revised interpretation of cortical areas building on the concept of neurobiological atoms that may be aggregated into larger units within and across modalities. We conclude by presenting an outlook on the implication of this revised concept for future mapping studies and raise some open questions in the context of brain parcellation.
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Affiliation(s)
- Simon B Eickhoff
- Institute of Systems Neuroscience, Medical Faculty, Heinrich-Heine University Düsseldorf, Germany; Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich-Heine University Düsseldorf, Germany; Institute of Neuroscience and Medicine (INM-1), Research Center Jülich, Germany.
| | - R Todd Constable
- Interdepartmental Neuroscience Program, Yale University, USA; Department of Radiology and Biomedical Imaging, Yale University, USA; Department of Neurosurgery, Yale University, USA
| | - B T Thomas Yeo
- Department of Electrical and Computer Engineering, ASTAR-NUS Clinical Imaging Research Centre, Singapore Institute for Neurotechnology and Memory Networks Program, National University of Singapore, Singapore; Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, USA; Centre for Cognitive Neuroscience, Duke-NUS Graduate Medical School, Singapore
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23
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Acute stress increases risky decisions and dampens prefrontal activation among adolescent boys. Neuroimage 2017; 146:679-689. [DOI: 10.1016/j.neuroimage.2016.08.067] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2016] [Revised: 08/22/2016] [Accepted: 08/31/2016] [Indexed: 11/23/2022] Open
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24
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Oberwelland E, Schilbach L, Barisic I, Krall SC, Vogeley K, Fink GR, Herpertz-Dahlmann B, Konrad K, Schulte-Rüther M. Look into my eyes: Investigating joint attention using interactive eye-tracking and fMRI in a developmental sample. Neuroimage 2016; 130:248-260. [PMID: 26892856 DOI: 10.1016/j.neuroimage.2016.02.026] [Citation(s) in RCA: 48] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2015] [Revised: 01/19/2016] [Accepted: 02/09/2016] [Indexed: 12/19/2022] Open
Abstract
Joint attention, the shared attentional focus of at least two people on a third significant object, is one of the earliest steps in social development and an essential aspect of reciprocal interaction. However, the neural basis of joint attention (JA) in the course of development is completely unknown. The present study made use of an interactive eye-tracking paradigm in order to examine the developmental trajectories of JA and the influence of a familiar interaction partner during the social encounter. Our results show that across children and adolescents JA elicits a similar network of "social brain" areas as well as attention and motor control associated areas as in adults. While other-initiated JA particularly recruited visual, attention and social processing areas, self-initiated JA specifically activated areas related to social cognition, decision-making, emotions and motivational/reward processes highlighting the rewarding character of self-initiated JA. Activation was further enhanced during self-initiated JA with a familiar interaction partner. With respect to developmental effects, activation of the precuneus declined from childhood to adolescence and additionally shifted from a general involvement in JA towards a more specific involvement for self-initiated JA. Similarly, the temporoparietal junction (TPJ) was broadly involved in JA in children and more specialized for self-initiated JA in adolescents. Taken together, this study provides first-time data on the developmental trajectories of JA and the effect of a familiar interaction partner incorporating the interactive character of JA, its reciprocity and motivational aspects.
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Affiliation(s)
- E Oberwelland
- Child Neuropsychology Section, Department of Child and Adolescent Psychiatry, Psychosomatics, and Psychotherapy, University Hospital RWTH Aachen, Germany; Translational Brain Research in Psychiatry and Neurology, Department of Child and Adolescent Psychiatry, Psychosomatics, and Psychotherapy, University Hospital Aachen, Germany; Cognitive Neuroscience, Institute of Neuroscience and Medicine (INM-3), Jülich Research Center, Germany.
| | - L Schilbach
- Department of Psychiatry, University Hospital Cologne, Germany; Max Planck Institute of Psychiatry, Munich, Germany
| | - I Barisic
- Department of Psychiatry, University Hospital Cologne, Germany; Department of Humanities, Social and Political Science, ETH Zurich, Switzerland
| | - S C Krall
- Child Neuropsychology Section, Department of Child and Adolescent Psychiatry, Psychosomatics, and Psychotherapy, University Hospital RWTH Aachen, Germany; Cognitive Neuroscience, Institute of Neuroscience and Medicine (INM-3), Jülich Research Center, Germany
| | - K Vogeley
- Cognitive Neuroscience, Institute of Neuroscience and Medicine (INM-3), Jülich Research Center, Germany; Department of Psychiatry, University Hospital Cologne, Germany
| | - G R Fink
- Cognitive Neuroscience, Institute of Neuroscience and Medicine (INM-3), Jülich Research Center, Germany; Department of Neurology, University Hospital Cologne, Germany
| | - B Herpertz-Dahlmann
- Department of Child and Adolescent Psychiatry, Psychosomatics, and Psychotherapy, University Hospital RWTH Aachen, Germany
| | - K Konrad
- Child Neuropsychology Section, Department of Child and Adolescent Psychiatry, Psychosomatics, and Psychotherapy, University Hospital RWTH Aachen, Germany; Cognitive Neuroscience, Institute of Neuroscience and Medicine (INM-3), Jülich Research Center, Germany
| | - M Schulte-Rüther
- Child Neuropsychology Section, Department of Child and Adolescent Psychiatry, Psychosomatics, and Psychotherapy, University Hospital RWTH Aachen, Germany; Translational Brain Research in Psychiatry and Neurology, Department of Child and Adolescent Psychiatry, Psychosomatics, and Psychotherapy, University Hospital Aachen, Germany; Cognitive Neuroscience, Institute of Neuroscience and Medicine (INM-3), Jülich Research Center, Germany
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